We're looking to overhaul our filtering for our users. As a starter we were looking to do some initial research online. I've hit a bit of an issue of understanding in doing so.
We currently operate 'subtractive' filtering:
- By default, everything is checked, user unchecks the data points they don't want to see.
Contrast to 'additive'/traditional filtering:
- default everything is unchecked, nothing is filtered in the group you've filtered unless something is applied. (below the filtering can be found on John Lewis' website)
I can't really find any information online, or uses cases as to when you'd use the first model, ideally we'd have it documented as to why this decision was made, and if not find out from our users, but that wasn't the task I was assigned in this overhaul.
The only scenario I could think of is if your users want to only filter out 1-2 areas of data, most of the time. Rather than filtering into specific areas, but this is just a scenario I've made up. Does it also just go against any universal standards of filtering?
Any help would be greatly appreciated.